The ultimate goal of mobile broadband is ubiquitous and sustainable provision of unlimited data rates to anyone or anything at anytime. Ultra Dense Network (UDN) is a promising next step to the successful introduction of Long Term Evolution (LTE) for wide area and local area accesses. The UDN can be deployed in areas with high traffic consumptions and thus provide an evolution towards the above goal. Due to overprovision of access nodes and thus low average load in the access network, the UDN creates ubiquitous access opportunities for providing users with desired data rates even under realistic assumption on user density and traffic.
The overprovision is achieved by an extremely dense grid of access nodes. Inter-access-node distances in the order of tens of meters or below are envisioned. In in-door deployments, one or more access nodes are possible in each room. In addition to increased network capacity, densification (via reduced transmit powers) also enables access to vast spectrums in millimeter-wave bands and thus increased data rates.
As the very first step of communication, synchronization is critical to the UDN. Here “synchronization” includes time-domain synchronization and/or frequency-domain synchronization. Compared with access link synchronization between an Access Node (AN, e.g., an evolved NodeB (eNB)) and a User Equipment (UE), it is more challenging to achieve backhaul link synchronization between ANs, which is necessary in the time domain for avoiding collisions between uplink and downlink (when Time Division Duplex (TDD) is applied) and achieving intelligent inter-cell interference coordination (e.g., enhanced Inter-Cell Interference Cooperation (eICIC)) and/or in the frequency domain for reducing handover latency and complexity in frequency error estimation. In traditional cellular networks, the backhaul link synchronization is achieved via wired connections, including e.g., packet based synchronization (Network Time Protocol (NTP) or Precision Time Protocol (PTP) (IEEE1588)) or Global Navigation Satellite System (GNSS) based synchronization (Global Positioning System (GPS) or Galileo). However, these solutions are not applicable in the UDN where ANs are deployed in an in-door scenario with wireless backhaul links.
Distributed Synchronization in Wireless Networks, IEEE Sig. Proc Magazine, 2008, discloses a solution for distributed synchronization in a wireless network. FIG. 1 shows a scenario where this solution is applied. As shown, each node broadcasts synchronization signals to all of its neighboring nodes and each node updates its local synchronization value based on synchronization signals received from all of its neighboring nodes. It is to be noted that the term “synchronization” as used herein refers to time-domain synchronization, frequency-domain synchronization, or both. Accordingly, “synchronization value” as used herein refers to time-domain synchronization value, frequency-domain synchronization value, or both. This solution requires a number of iterations before the synchronization values of the nodes converge (i.e., the nodes reach a synchronized state).
According to this distributed synchronization solution, at a node i, the synchronization value of a node j is estimated, e.g., by utilizing a non-coherent detection algorithm, e.g., Maximum Likelihood (ML) algorithm or Minimum Mean Square Error (MMSE) algorithm. The estimated synchronization value of the node j is represented here as ŝj which may include a frequency-domain synchronization value {circumflex over (α)}j and/or a time-domain synchronization value {circumflex over (β)}j.
Then, the node i updates its local synchronization value according to the following iteration equation:
                                          s            i                    ⁡                      (                          n              +              1                        )                          =                                                            s                i                            ⁡                              (                n                )                                      +                                          ∑                                  j                  =                  1                                M                            ⁢                                                          ⁢                                                                    s                    ^                                    j                                ⁡                                  (                  n                  )                                                                          M            +            1                                              (        1        )            where n is the iteration index, si is the synchronization value of the node i and M is the number of neighboring nodes.
Equivalently, Equation (1) can be rewritten as:
                                          α            i                    ⁡                      (                          n              +              1                        )                          =                                                                              α                  i                                ⁡                                  (                  n                  )                                            +                                                ∑                                      j                    =                    1                                    M                                ⁢                                                                  ⁢                                                                            α                      ^                                        j                                    ⁡                                      (                    n                    )                                                                                      M              +              1                                ⁢                                          ⁢          and          ⁢                      /                    ⁢          or                                    (        2        )                                                      β            i                    ⁡                      (                          n              +              1                        )                          =                                                            β                i                            ⁡                              (                n                )                                      +                                          ∑                                  j                  =                  1                                M                            ⁢                                                          ⁢                                                                    β                    ^                                    j                                ⁡                                  (                  n                  )                                                                          M            +            1                                              (        3        )            where αi and βi denote the frequency-domain and time-domain synchronization values of the node i, respectively.
The node i transmits synchronization signals to its neighboring nodes periodically.
FIG. 2 shows a simulation result of an iterative process for time-domain synchronization values of nodes in a network. In this simulation, it is assumed that there are 11*11=121 nodes distributed over a square area and the initial time-domain synchronization values of these nodes are randomly distributed within a range of one symbol length (2.778 μs). The horizontal axis of FIG. 2 represents the number of iterations and the vertical axis of FIG. 2 represents average error of the time-domain synchronization values of the nodes in Cyclic Prefix (CP) lengths (1 CP length=347 ns). The network can be considered to reach a synchronized state when the average error is smaller than 1 CP length. It can be seen from FIG. 2 that, after 6 iterations, the average error becomes about 0.8 CP lengths and the network can be considered as synchronized.
However, the distributed synchronization solution suffers from a “new arrival” problem. For example, when a new node arrives (e.g., a new node is powered on or activated) after all the nodes in the network have reached the synchronized state, the arrival of the new node may have significant impact on the synchronization in the network. FIG. 3 shows a simulation result explaining the “new arrival” problem. The horizontal axis of FIG. 3 represents the number of iterations and the vertical axis of FIG. 3 represents average error of the time-domain synchronization values of the nodes in Ts (sampling period, 1 Ts=0.4518 ns). In this simulation, a new node arrives at the 50-th iteration and cause a significant fluctuation in the average error. It can be seen from FIG. 3 that the network is re-synchronized at the 52-th iteration when the average error becomes 358.8 Ts≈0.4671 CP lengths. The “new arrival” problem also exists in frequency-domain synchronization, for which detail descriptions will be omitted here.
In addition, it is generally desired to reach such synchronized state as soon as possible. In order to accelerate the iterative process, each node shall transmit its synchronization signals at a relatively short period, which, however, is disadvantageous from the perspective of power consumption.
There is thus a need for an improved solution for distributed synchronization.